Abstract
The African American Study of Kidney Disease and Hypertension (AASK), a randomized double-blinded treatment trial, was motivated by the high rate of hypertension-related renal disease in the African-American population and the scarcity of effective therapies. This study describes a pattern-based classification approach to predict the rate of decline of kidney function using surface-enhanced laser desorption ionization/time of flight proteomic data from rapid and slow progressors classified by rate of change in glomerular filtration rate. An accurate classification model consisting of 7 out of 5,751 serum proteomic features is constructed by applying the logical analysis of data (LAD) methodology. On cross-validation by 10-folding, the model was shown to have an accuracy of 80.6 ± 0.11%, sensitivity of 78.4 ± 0.17%, and specificity of 78.5 ± 0.16%. The LAD discriminant is used to identify the patients in different risk groups. The LAD risk scores assigned to 116 AASK patients generated a receiver operating curves curve with AUC 0.899 (CI 0.845–0.953) and outperforms the risk scores assigned by proteinuria, one of the best predictors of chronic kidney disease progression.
Highlights
Chronic kidney disease (CKD), defined by reduced glomerular filtration rate (GFR), proteinuria, or structural kidney disease, is a worldwide growing public health problem
The main goal of this study is to identify a small set of SELDI-TOF peaks to develop logical analysis of data (LAD) models for the purpose of (i) classifying an individual observation as a rapid or slow progressor based on serum proteomic features and (ii) predicting the progression of CKD
We present an unbiased pattern-based classification approach to predict the rate of decline of kidney function in CKD using a SELDI-TOF proteomics data set
Summary
Chronic kidney disease (CKD), defined by reduced glomerular filtration rate (GFR), proteinuria, or structural kidney disease, is a worldwide growing public health problem. Many subjects with renal disease of most etiologies progress to renal failure and end-stage renal disease (ESRD) requiring dialysis or renal transplantation, despite the best current therapies [1,2,3,4,5,6,7]. Identification and characterization of novel biomarkers and targets of therapy for the ESRD patients remains a major focus of the current research in kidney disease and has been the objective of a number of studies, such as the African American Study of Kidney Disease and Hypertension (AASK). Data from AASK showed that despite what is still considered optimal therapy of renin–angiotensin system blockade and reduction of systolic blood pressure to less than 130 mmHg, more than half of the patients developed the composite outcome of doubling of Cr, ESRD, or death [7]. Several possible interventions, including controlling blood pressure [6], treating diabetes [3], modifying
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